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01-01-2020 | APPLIED PROBLEMS | Issue 1/2020

Pattern Recognition and Image Analysis 1/2020

Application of Image Processing in Detection of Bone Diseases Using X-rays

Journal:
Pattern Recognition and Image Analysis > Issue 1/2020
Authors:
Sikander Khan, Tariq Rahim Soomro, M. Mansoor Alam
Important notes
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Mr. Sikander Khan is working with the department of Computer Science at Shaheed Zulfikar Ali Bhutto Institute of Science and Technology and recently completed his MS in Computer Science from Institute of Business Management, Karachi. He has many interdisciplinary research projects related to biotechnology and robotics. His research interest are image analysis and biomedical image processing.
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Dr. Tariq Rahim Soomro, Professor of Computer Science and Dean at College of Computer Science and Information Systems, Institute of Business Management, has received B.Sc. (Hons) and M.Sc. degrees in Computer Science from University of Sindh, Jamshoro, Pakistan and his PhD in Computer Applications from Zhejiang University, Hangzhou, China. He has more than 25 years of extensive and diverse experience as an administrator, computer programmer, researcher, and teacher. His research focuses on GIS, IDNS, distance education, E‑commerce, multimedia, UNICODE, WAP, P2P, bioinformatics, ITIL, cloud computing, green computing, big data, IoT, quality of software, telemedicine, VoIP, databases, programming, and higher education. He has published in these areas with over 80 peer-reviewed papers.
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Dr. Muhammad M. Alam is a Professor of Computer Science. He is working as an Associate Dean in CCSIS and HoD Mathematics, Statistics and Computer Science Departments. Dr. Alam is enjoying 20 years of research and teaching experience in Canada, England, France, Malaysia, Saudi Arabia and Bahrain and authored 150+ research articles, which are published in well reputed journals of high impact factor, Springer Link book chapters, Scopus indexed journals, and IEEE conferences. He has honor to work as an online laureate (facilitator) for MSIS program run by Colorado State University, USA and Saudi Electronic University, KSA. Dr. Alam has also established research collaboration with Universiti Kuala Lumpur (UniKL) and Universiti Malaysia Pahang (UMP). Currently, Dr. Alam is also working as an adjunct professor in UniKL and supervising 12 PhD students.

Abstract

This study compares published algorithms for the detection of bone diseases particularly osteoporosis (which is characterized by low level of bone mineral density and porosity due to microarchitectural deterioration) with claimed accuracy on based on the author selected dataset. In this study common dataset is used to verify accuracy and performance of the published algorithms by comparing the output results published by the authors and the results gathered and compiled by this study. Features like contrast, correlation, homogeneity, entropy, energy along with standard deviation, range, skewness are calculated from Gray-Level Co-occurrence Matrix (GLCM) technique. Study also implement all algorithms published by the authors and tested with common dataset containing digital images of X-ray femur (left and right leg femur; both). The research concludes that the standard deviation, image contrast and specifically energy with entropy plays a vital role in determining the disease by performing Haralick features textural analysis on plain (Non-DEXA) radiographs.

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